Centre for Digital Governance
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“Hashjacking” the Debate: Polarisation Strategies of Germany’s Political Far-Right on Twitter
(2019)
Twitter is a digital forum for political discourse. The emergence of phenomena like fake news and hate speech has shown that political discourse on micro-blogging can become strongly polarised by algorithmic enforcement of selective perception. Recent findings suggest that some political actors might employ strategies to actively facilitate polarisation on Twitter. With a network approach, we examine the case of the German far-right party Alternative für Deutschland (AfD) and their potential use of a “hashjacking” strategy (The use of someone else’s hashtag in order to promote one’s own social media agenda.). Our findings suggest that right-wing politicians (and their supporters/retweeters) actively and effectively polarise the discourse not just by using their own party hashtags, but also by “hashjacking” the political party hashtags of other established parties. The results underline the necessity to understand the success of right-wing parties, online and in elections, not entirely as a result of external effects (e.g. migration), but as a direct consequence of their digital political communication strategy.
Political campaign activities are increasingly digital. A crucial part of digital campaigning is communication efforts on social media platforms. As a forum for political discourse and political communication, parties and candidates on Twitter share public messages and aim to attract media attention and persuade voters. Party or prominent candidate hashtags are a central element of the campaign communication strategy since journalists and citizens search for these hashtags to follow the current debate concerning the hashed party or political candidate. Political elites and partisans use social media strategically, e.g., to link their messages to a broader debate, increase the visibility of messages, criticize other parties, or take over their hashtags (hashjacking). This study investigates the cases of the most recent 2017 and 2021 German federal elections called 'Bundestagswahlen'. The investigation (1) identifies communities of partisans in retweet networks in order to analyze the polarization of the most prominent hashtags of parties, 2) assesses the political behavior by partisan groups that amplify messages by political elites in these party networks, and 3) examines the polarization and strategic behavior of the identified partisan groups in the broader election hashtag debates using #BTW17 and #BTW21 as the prominent hashtags of the 2017 and 2021 elections. While in 2017, the far-right party 'Alternative für Deutschland' (AfD) and its partisans are in an isolated community, in 2021, they are part of the same community as the official party accounts of established conservative and liberal parties. This broader polarization may indicate changes in the political ideology of these actors. While the overall activity of political elites and partisans increased between 2017 and 2021, AfD politicians and partisans are more likely to use other party hashtags, which resulted in the polarization of the observed parts of the German political twitter sphere. While in 2017, the AfD polarized German Twitter, 2021 shows a broader division along the classical left–right divide.
Social media companies rely on user agreements as one means to manage content produced by users. While much has been written on user agreements and community standards of U.S.-based social media, surprisingly little is known about Chinese user agreements and their implications. We compare terms of services as well as privacy policies of WeChat and Weibo between 2014 and 2019 using their U.S. counterparts WhatsApp and Twitter as a benchmark. We find that Chinese user agreements reveal a territorial-based understanding of content management differentiating between PRC and non-PRC users based on language, IP address and country of citizenship. Second, Chinese social media companies are surprisingly transparent about what content can be published, which has implications for self-censorship among users. Third, changes in PRC user agreements reflect Xi Jinping’s tightening control of the Internet. Finally, U.S.-based platforms have moved towards content management that differs by region, thus becoming more similar to the Chinese approach over time.
Research on smart cities is still at an early stage. The conjecture of this article is that smart city strategies and their impacts will inevitably vary across contexts; however, the debate still lacks an analytical toolkit that guides the exploration of such varieties (and similarities) of smart cities. Combining existing research on the governance of smart cities with theories of business–state relations from political economy, this article develops an analytical framework and typology that captures varieties (and similarities) of smart city policies and governance. We apply this framework to four illustrative cases: Prague, Barcelona, Berlin, and Rio de Janeiro.
Why does online public opinion emerge in some social media more easily than in others? Building on research on authoritarian deliberation, we describe spaces for political discussion in Chinese cyberspace in terms of interactivity, which results in different forms of political discussion. Drawing on semi-structured qualitative expert interviews with information and communications technology professionals at Tencent, Weibo, and Baidu, we explain how major social media differ in terms of their structure and the company’s motivation. We specify which features are more likely to facilitate the emergence of online public opinion in Chinese social media and provide preliminary evidence from 92 semi-structured interviews with Internet users.
The governments of today are not able to transform and adapt to changes in the world around them, as demanded by their constituents. The nature of work, value of public goods, and the constant bombardment of crises are making the old bureaucratic structures obsolete.
Agile Government is an emerging theme, that of government-wide reinvention for adaptiveness and responsiveness. It places the accountability, delivery, capture, design and creation of public value at the heart of the government. The concept of agile government is confused with terms like Agile Manifesto, agile governance, agility among others, and because of this, needs some unpacking.
This book is a deep dive into this topic. It offers insights from the theoretical development of the topic of agile government, some lessons from government practices around the world, and ongoing academic and policy research. The project is spearheaded by the Mohammed Bin Rashid School of Government, which is the first teaching and research institution in the Arab world focusing on public policy and governance.
This dissertation explores corporatization–the provision of public services by publicly-owned companies–as a specific public management reform that has strongly been endorsed in the last decades. However, despite the significance of corporatization in public administration and the controversy over its viability as a strategy for enhancing public service provision, there is limited empirical research on its trajectory and associated effects. This dissertation fills this important gap in the literature by examining the causes, dynamics, and consequences of corporatization. It challenges the claim that we are witnessing a resurgence of the state in recent years, resulting in a pendulum shift from the private to the public sector. A mixed-methods approach is employed to analyze three original datasets from English and German local government contexts. Theoretical perspectives rooted in rational choice are complemented by those accounting for irrational ambiguity to capture the unique ambidexterity of corporatization. After clarifying the theoretical background in Chapter 1, this exploration unfolds across three empirical chapters. Chapter 2 investigates what drives corporatization. It reveals that ownership structures in corporatization have become increasingly complex and political–rather than economic–incentives may explain shifts toward indirect municipal ownership. Chapter 3 examines what causes corporatization to reverse. It shows that a return of services to the core local government after a company closes is less likely than other forms of service provision, while the type of service is the factor that matters most for termination decisions. Chapter 4 analyzes how local governments experience and cope with reverse corporatization. Local governments and their employees evidently and mutually impact the return process, which can induce private sector-informed change within the bureaucracy, albeit with limited transformative power. Ultimately, this dissertation finds no clear evidence of a pendulum shift toward the local public sector. This conclusion follows from conceptual and empirical differentiation and depends on how corporatization is framed, as well as on the specific country, service type, and dimension of public influence considered. It also suggests that the notion of the pendulum shift needs reevaluation. For practitioners, this holds several implications that encourage optimism about reform, and advise against an arbitrary approach to diversifying costs.
In today's world, disasters, both natural and manmade, are becoming increasingly frequent, and new solutions are of a compelling need to provide and disseminate information about these disasters to the public and concerned authorities in an effective and efficient manner. One of the most frequently used ways for information dissemination today is through social media, and when it comes to real-time information, Twitter is often the channel of choice. Thus, this paper discusses how Big Data Analytics (BDA) can take advantage of information streaming from Twitter to generate alerts and provide information in real-time on ongoing disasters. The paper proposes TAGS (Twitter Alert Generation System), a novel solution for collecting and analyzing social media streaming data in realtime and subsequently issue warnings related to ongoing disasters using a combination of Hadoop and Spark frameworks. The paper tests and evaluates the proposed solution using Twitter data from the 2018 earthquake in Palu City, Sulawesi, Indonesia. The proposed architecture was able to issue alert messages on various disaster scenarios and identify critical information that can be utilized for further analysis. Moreover, the performance of the proposed solution is assessed with respect to processing time and throughput that shows reliable system efficiency.